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Functional and Topological Conditions for Explosive Synchronization Develop in Human Brain Networks with the Onset of Anesthetic-Induced Unconsciousness

机译:麻醉诱导的无意识发作在人脑网络中爆炸同步发展的功能和拓扑条件。

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摘要

Sleep, anesthesia, and coma share a number of neural features but the recovery profiles are radically different. To understand the mechanisms of reversibility of unconsciousness at the network level, we studied the conditions for gradual and abrupt transitions in conscious and anesthetized states. We hypothesized that the conditions for explosive synchronization (ES) in human brain networks would be present in the anesthetized brain just over the threshold of unconsciousness. To test this hypothesis, functional brain networks were constructed from multi-channel electroencephalogram (EEG) recordings in seven healthy subjects across conscious, unconscious, and recovery states. We analyzed four variables that are involved in facilitating ES in generic, non-biological networks: (1) correlation between node degree and frequency, (2) disassortativity (i.e., the tendency of highly-connected nodes to link with less-connected nodes, or vice versa), (3) frequency difference of coupled nodes, and (4) an inequality relationship between local and global network properties, which is referred to as the suppressive rule. We observed that the four network conditions for ES were satisfied in the unconscious state. Conditions for ES in the human brain suggest a potential mechanism for rapid recovery from the lightly-anesthetized state. This study demonstrates for the first time that the network conditions for ES, formerly shown in generic networks only, are present in empirically-derived functional brain networks. Further investigations with deep anesthesia, sleep, and coma could provide insight into the underlying causes of variability in recovery profiles of these unconscious states.
机译:睡眠,麻醉和昏迷具有许多神经功能,但恢复情况完全不同。为了了解网络级别的意识丧失可逆性的机制,我们研究了意识状态和麻醉状态下逐渐过渡和突然转变的条件。我们假设人脑网络中爆炸同步(ES)的条件将在麻醉后的大脑中刚刚超过无意识的阈值。为了检验该假设,从七个通道的有意识,无意识和恢复状态的健康受试者的多通道脑电图(EEG)记录中构建了功能性大脑网络。我们分析了在普通的非生物网络中促进ES涉及的四个变量:(1)节点度和频率之间的相关性,(2)离散性(即,高连接度节点与低连接度节点链接的趋势,反之亦然),(3)耦合节点的频差,以及(4)本地和全局网络属性之间的不平等关系,这称为抑制规则。我们观察到在无意识状态下满足ES的四个网络条件。人脑中ES的状况提示了从轻度麻醉状态快速恢复的潜在机制。这项研究首次证明了ES的网络条件(以前仅在通用网络中显示)存在于根据经验得出的功能性大脑网络中。深层麻醉,睡眠和昏迷的进一步研究可以深入了解这些无意识状态的恢复状况变化的根本原因。

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